feat(notebook): more docs, better defaults
Browse files
ai_assisted_data_curation.ipynb
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"### Use a Specific Harmonization Approach to get Suggestions"
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{
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"cell_type": "code",
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"execution_count": null,
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"\n",
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"harmonization_approach = SimilaritySearchInMemoryVectorDb(\n",
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" # A unique name for this file and embedding algorithm within the limits of the length required by the in-memory vectostore\n",
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" vectordb_persist_directory_name=f\"{os.path.basename(target_file)[:53]}-{embedding_fn.
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" input_target_model=input_target_model,\n",
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" embedding_function=embedding_fn,\n",
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" batch_size=batch_size,\n",
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")\n",
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"\n",
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"# set threshold low to just get top properties no matter what\n",
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"score_threshold = 0\n",
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"\n",
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"source": [
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"> **Don't see the table or see an error above?** Try restarting the kernel, then try restarting jupyter lab (if that's what you're using). The installs for AnyWidgets might not be picked up yet.\n",
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"\n",
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"> **
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"\n",
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"> **Using VS Code Jupyter Extension?**
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]
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},
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{
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"### Use a Specific Harmonization Approach to get Suggestions"
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]
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},
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{
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"cell_type": "markdown",
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"id": "deb30aa8",
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"metadata": {},
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"source": [
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"We are using a specially trained embedding model created by UChicago CTDS, which is optimized for variable-level mapping. \n",
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"\n",
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"You can view details of the model here: https://huggingface.co/uc-ctds/bge-large-en-v1.5-bio-mapping"
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]
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},
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"cell_type": "code",
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"execution_count": null,
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"\n",
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"harmonization_approach = SimilaritySearchInMemoryVectorDb(\n",
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" # A unique name for this file and embedding algorithm within the limits of the length required by the in-memory vectostore\n",
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" vectordb_persist_directory_name=f\"{os.path.basename(target_file)[:53]}-{embedding_fn.model_name.split(\"/\")[-1][:5]}-0\",\n",
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" input_target_model=input_target_model,\n",
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" embedding_function=embedding_fn,\n",
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" batch_size=batch_size,\n",
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")\n",
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"\n",
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"# By default, get all options (will eventually sort by most relevant)\n",
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"max_suggestions_per_property = len(harmonization_approach.vectorstore.get()[\"ids\"])\n",
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"# max_suggestions_per_property = 10\n",
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"\n",
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"# set threshold low to just get top properties no matter what\n",
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"score_threshold = 0\n",
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"\n",
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"source": [
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"> **Don't see the table or see an error above?** Try restarting the kernel, then try restarting jupyter lab (if that's what you're using). The installs for AnyWidgets might not be picked up yet.\n",
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"\n",
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"> **Colors / Theme off?** If you're using a dark theme, you might need to switch to light for the table to display properly (or vice-versa).\n",
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"\n",
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"> **Using VS Code Jupyter Extension?** Any Embedded links (if they exist) might not work"
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]
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},
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{
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